Urology

Attention-enabled 3D boosted convolutional neural networks for semantic CT segmentation using deep supervision.

A deeply supervised attention-enabled boosted convolutional neural network (DAB-CNN) is presented as a superior alternative to current state-of-the-art convolutional neural networks (CNNs) for semantic CT segmentation. Spatial attention gates (AGs) were incorporated into a novel 3D cascaded CNN framework to prioritize relevant anatomy and suppress redundancies within the network. Due to the comple...

Changes in clinical indicators related to the transition from dialysis to kidney transplantation-data from the ERA-EDTA Registry.

BACKGROUND: Kidney transplantation should improve abnormalities that are common during dialysis treatment, like anaemia and mineral and bone disorder. However, its impact is incompletely understood. We therefore aimed to assess changes in clinical indicators after the transition from chronic dialysis to kidney transplantation.

[Renal graft survival in patients transplanted from organs of deceased donors].

BACKGROUND: In Mexico, out of the total number of transplants it was reported, in 2014, a frequency of 29% of deceased donor renal transplantation (DD...

Combination possibility and deep learning model as clinical decision-aided approach for prostate cancer.

This study aims to introduce as proof of concept a combination model for classification of prostate cancer using deep learning approaches. We utilized...

A Radical Proposition: Opioid-sparing Prostatectomy.

Radical prostatectomy has largely become a procedure requiring a single day in the hospital with improving convalescence. Pre-operative counseling on ...

Artificial intelligence and machine learning for predicting acute kidney injury in severely burned patients: A proof of concept.

BACKGROUND: Burn critical care represents a high impact population that may benefit from artificial intelligence and machine learning (ML). Acute kidn...

Automatic gas detection in prostate cancer patients during image-guided radiation therapy using a deep convolutional neural network.

PURPOSE: The detection of intestinal/rectal gas is very important during image-guided radiation therapy (IGRT) of prostate cancer patients because int...

Incorporating dosimetric features into the prediction of 3D VMAT dose distributions using deep convolutional neural network.

An accurate prediction of achievable dose distribution on a patient specific basis would greatly improve IMRT/VMAT planning in both efficiency and qua...

Recognition of early and late stages of bladder cancer using metabolites and machine learning.

INTRODUCTION: Bladder cancer (BCa) is one of the most common and aggressive cancers. It is the sixth most frequently occurring cancer in men and its r...

Detection and Classification of Novel Renal Histologic Phenotypes Using Deep Neural Networks.

With the advent and increased accessibility of deep neural networks (DNNs), complex properties of histologic images can be rigorously and reproducibly...

Effects of early high-dose erythropoietin on acute kidney injury following cardiac arrest: exploratory analyses from an open-label randomized trial.

BACKGROUND: Acute kidney injury (AKI) is frequent in patients resuscitated from cardiac arrest (CA) and may worsen outcome. Experimental data suggest ...

Comparison of autoregressive integrated moving average model and generalised regression neural network model for prediction of haemorrhagic fever with renal syndrome in China: a time-series study.

OBJECTIVES: Haemorrhagic fever with renal syndrome (HFRS) is a serious threat to public health in China, accounting for almost 90% cases reported glob...

The mid-term effect of left ventricular assist devices on renal functions.

BACKGROUND: In this study, we aimed to investigate the mid-term effects of left ventricular assist devices on kidney functions.

Computer-Aided Diagnosis and Clinical Trials of Cardiovascular Diseases Based on Artificial Intelligence Technologies for Risk-Early Warning Model.

The use of artificial intelligence in medicine is currently an issue of great interest, especially with regard to the diagnostic or predictive analysi...

Time to Move On: The Impending Need for a New Disease-specific Comorbidity Index for Bladder Cancer Patients Undergoing Robot-assisted Radical Cystectomy.

The Charlson comorbidity index is an outdated comorbidity assessment tool which is not disease specific and is not applicable to contemporary BCa pati...

Machine learning classifiers can predict Gleason pattern 4 prostate cancer with greater accuracy than experienced radiologists.

OBJECTIVE: The purpose of this study was: To test whether machine learning classifiers for transition zone (TZ) and peripheral zone (PZ) can correctly...

Impact of age on cardiovascular drug use in patients with chronic kidney disease.

BACKGROUND: Elderly patients with chronic kidney disease (CKD) are often excluded from clinical trials; this may affect their use of essential drugs f...

Automated Bone Scan Index as an Imaging Biomarker to Predict Overall Survival in the Zometa European Study/SPCG11.

BACKGROUND: Owing to the large variation in treatment response among patients with high-risk prostate cancer, it would be of value to use objective to...

Update on the Urology Tag Ontology: Standardized Hashtags for Social Media in Urology.

Prediction of Nephropathy in Type 2 Diabetes: An Analysis of the ACCORD Trial Applying Machine Learning Techniques.

Applying data mining and machine learning (ML) techniques to clinical data might identify predictive biomarkers for diabetic nephropathy (DN), a commo...